Ahluwalia Kabir, Ebright Brandon, Chow Kingsley, Dave Priyal, Mead Andrew, Poblete Roy, Louie Stan G, Asante Isaac
School of Pharmacy, University of Southern California, Los Angeles, CA 90089, USA.
Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Metabolites. 2022 Apr 7;12(4):333. doi: 10.3390/metabo12040333.
The lipidome has a broad range of biological and signaling functions, including serving as a structural scaffold for membranes and initiating and resolving inflammation. To investigate the biological activity of phospholipids and their bioactive metabolites, precise analytical techniques are necessary to identify specific lipids and quantify their levels. Simultaneous quantification of a set of lipids can be achieved using high sensitivity mass spectrometry (MS) techniques, whose technological advancements have significantly improved over the last decade. This has unlocked the power of metabolomics/lipidomics allowing the dynamic characterization of metabolic systems. Lipidomics is a subset of metabolomics for multianalyte identification and quantification of endogenous lipids and their metabolites. Lipidomics-based technology has the potential to drive novel biomarker discovery and therapeutic development programs; however, appropriate standards have not been established for the field. Standardization would improve lipidomic analyses and accelerate the development of innovative therapies. This review aims to summarize considerations for lipidomic study designs including instrumentation, sample stabilization, data validation, and data analysis. In addition, this review highlights how lipidomics can be applied to biomarker discovery and drug mechanism dissection in various inflammatory diseases including cardiovascular disease, neurodegeneration, lung disease, and autoimmune disease.
脂质组具有广泛的生物学和信号传导功能，包括作为细胞膜的结构支架以及启动和消除炎症。为了研究磷脂及其生物活性代谢物的生物活性，需要精确的分析技术来鉴定特定脂质并量化其水平。使用高灵敏度质谱（MS）技术可以实现一组脂质的同时定量，在过去十年中，该技术取得了显著进步。这开启了代谢组学/脂质组学的力量，能够对代谢系统进行动态表征。脂质组学是代谢组学的一个子集，用于多分析物鉴定和内源性脂质及其代谢物的定量。基于脂质组学的技术有潜力推动新型生物标志物的发现和治疗开发项目；然而，该领域尚未建立适当的标准。标准化将改善脂质组学分析并加速创新疗法的开发。本综述旨在总结脂质组学研究设计的注意事项，包括仪器设备、样品稳定、数据验证和数据分析。此外，本综述强调了脂质组学如何应用于各种炎症性疾病（包括心血管疾病、神经退行性疾病、肺部疾病和自身免疫性疾病）的生物标志物发现和药物机制剖析。
